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KDD
2004
ACM
139views Data Mining» more  KDD 2004»
14 years 6 months ago
Learning a complex metabolomic dataset using random forests and support vector machines
Metabolomics is the omics science of biochemistry. The associated data include the quantitative measurements of all small molecule metabolites in a biological sample. These datase...
Young Truong, Xiaodong Lin, Chris Beecher
SCFBM
2008
138views more  SCFBM 2008»
13 years 5 months ago
Epigrass: a tool to study disease spread in complex networks
Background: The construction of complex spatial simulation models such as those used in network epidemiology, is a daunting task due to the large amount of data involved in their ...
Flávio C. Coelho, Oswaldo G. Cruz, Cl&aacut...
CCGRID
2004
IEEE
13 years 9 months ago
Evolutionary molecular structure determination using Grid-enabled data mining
A new computational framework is developed for the evolutionary determination of molecular crystal structures using the Shake-and-Bake methodology. Genetic algorithms are performe...
Mark L. Green, Russ Miller
BMCBI
2005
134views more  BMCBI 2005»
13 years 5 months ago
Inherited disorder phenotypes: controlled annotation and statistical analysis for knowledge mining from gene lists
Background: Analysis of inherited diseases and their associated phenotypes is of great importance to gain knowledge of underlying genetic interactions and could ultimately give cl...
Marco Masseroli, Osvaldo Galati, Mauro Manzotti, K...
ACRI
2004
Springer
13 years 11 months ago
Mining Ecological Data with Cellular Automata
This paper introduces a Cellular Automata (CA) approach to spatiotemporal data mining (STDM). The recently increasing interest in using Genetic Algorithms and other evolutionary te...
Alexander Campbell, Binh Pham, Yu-Chu Tian